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Erschienen in:
2009 | OriginalPaper | Buchkapitel
MIRACLE at ImageCLEFannot 2008: Nearest Neighbour Classification of Image Feature Vectors for Medical Image Annotation
verfasst von : Sara Lana-Serrano, Julio Villena-Román, José Carlos González-Cristóbal, José Miguel Goñi-Menoyo
Erschienen in: Evaluating Systems for Multilingual and Multimodal Information Access
Verlag: Springer Berlin Heidelberg
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This paper describes the participation of MIRACLE research consortium at the ImageCLEF Medical Image Annotation task of ImageCLEF 2008. During the last year, our own image analysis system was developed, based on MATLAB. This system extracts a variety of global and local features including histogram, image statistics, Gabor features, fractal dimension, DCT and DWT coefficients, Tamura features and co-occurrence matrix statistics. A classifier based on the k-Nearest Neighbour algorithm is trained on the extracted image feature vectors to determine the IRMA code associated to a given image. The focus of our participation was mainly to test and evaluate this system in-depth and to compare among diverse configuration parameters such as number of images for the relevance feedback to use in the classification module.